BIG DATA SCORING2015

OUR VISION

BRING LENDING INTO THE DIGITAL INFORMATION AGE

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ATTRACTING THE NEXT GENERATION OF AUTO BUYERS

LENDING TO THE UNDERBANKED NON-PRIME CUSTOMERS

23% of UK population, that is

15m people

25% of USA population,

that is 83m people

…

13% of UK population, that is

8m people

20% of USA population,

that is 64m people

…

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Credit scoring for the past 20 years…

FICO

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Credit scoring 2.0

FICO

6Source: Telefonica Millennial Study

People aged 18-33 spend on average 6h a

day online

Studied abroad

Doesn’t use credit cards

No student loan

Fan of Apple Pay

Irregular income

No mortgage

Has a blog

Fan of social media

Freelancedesigner

Loves hissmartphone

Has tons of friends

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Social media

Device infoInternet service

provider

Google searchresults

Governmentdatabases

Onlinebehavior Employer info

Blogs

10

Social media

11

Freelance jobs

12

Behavior

13

Device

Government data

15

Location

16

Public online data

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Current situation

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With Big Data Scoring

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Case 1 – credit loss decrease 34.6%BEFORE• Client: non-bank consumer

lender in CEE• Current scoring: regression

based models• Current data: (1) loan

application, (2) negative credit bureau data, (3) positive credit bureau data

• Credit loss: 7.5% (accepted clients in scorebands 7-10)

AFTER ADDITION OF BIG DATA

While accepting the same amount of loan applications,

credit loss dropped by 34.6% to 4.9%

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Case 2 – also works with offline clientsBEFORE• Client: non-bank consumer

lender in CEE• Current scoring: regression

based models• Current data: (1) loan

application, (2) negative credit bureau data, (3) positive credit bureau data

• Credit loss: 6.2% (accepted clients in scorebands 4-10)

AFTER ADDITION OF PARTIAL BIG DATA SCORE TO OFFLINE

CLIENTS

While accepting the same amount of loan applications,

credit loss dropped by 9.7% to 5.6%

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Thank you!Erki Kerterki.kert@bigdatascoring.com+44 7852 266613

Big Data Scoring Ltd1 Canada Square, Canary WharfLondon, E14 5AB